DataBricks Data Solutions Architect (Only Visa Independent Candidate/W2)

Key Responsibilities:

• Define enterprise data architecture, cloud data-platform strategy, technical standards, and modernization roadmaps.
• Architect Azure Databricks Lakehouse environments using Delta Lake, medallion architecture, Unity Catalog, and scalable ingestion and transformation patterns.
• Design end-to-end Azure data ecosystems using Databricks, Azure Data Factory, ADLS Gen2, Azure Synapse Analytics, and Power BI.
• Develop architectural patterns for batch, micro-batch, and real-time data processing using PySpark, Kafka, Airflow, and Azure-native services.
• Design dimensional data models, including star and snowflake schemas, conformed dimensions, semantic layers, and enterprise data warehouse structures.
• Establish data-governance, quality, metadata, lineage, security, access-control, and compliance frameworks.
• Optimize Databricks and distributed-processing environments through partitioning, clustering, data-skew remediation, schema evolution, workload tuning, and cost controls.
• Design Terraform-based infrastructure and CI/CD processes using Azure DevOps or comparable tools.
• Support data migrations, legacy-platform modernization, analytics enablement, and AI/ML data initiatives.
• Present architecture designs, standards, recommendations, and technical decisions to engineering teams, architecture review boards, business stakeholders, and executive leadership.
• Proactively identify architectural risks, scalability concerns, governance gaps, and modernization opportunities.

 

Required Experience:

• Senior-level experience as a Data Solutions Architect, Data Architect, Cloud Data Architect, or Databricks Architect.
• Strong, recent Azure Databricks architecture experience.
• Azure data architecture certification or relevant Microsoft Azure architecture certification.
• Enterprise Lakehouse and data warehouse architecture.
• Azure Data Factory, ADLS Gen2, and Azure Synapse Analytics.
• PySpark and distributed data-processing architecture.
• Dimensional data modeling, including star and snowflake schemas.
• Data governance, data quality, metadata management, security, and compliance.
• Databricks performance optimization and platform scalability.
• Terraform, Infrastructure as Code, Azure DevOps, and CI/CD.
• Power BI and enterprise analytics integration.
• Strong communication, documentation, and stakeholder-management skills.
• Proactive architecture leadership with the ability to drive strategy and execution independently.

 

Preferred Experience:

• Snowflake architecture.
• Kafka and real-time streaming.
• AWS data services, including Glue, Lambda, S3, Kinesis, or Redshift.
• Multi-cloud data-platform architecture.
• Cloud data migrations and modernization programs.
• AI/ML data enablement.
• Utility, energy, operational technology, SCADA, or other regulated-industry experience.